Real-time Realistic Rain Rendering

Artistic outdoor filming and rendering need to choose specific weather conditions in order to properly trigger the audience reaction; for instance, rain, one of the most common conditions, is usually employed to transmit a sense of unrest. Synthetic methods to recreate weather are an important avenue to simplify and cheapen filming, but simulations are a challenging problem due to the variety of different phenomena that need to be computed. Rain alone involves raindrops, splashes on the ground, fog, clouds, lightnings, etc. We propose a new rain rendering algorithm that uses and extends present state of the art approaches in this field. The scope of our method is to achieve real-time renders of rain streaks and splashes on the ground, while considering complex illumination effects and allowing an artistic direction for the drops placement. Our algorithm takes as input an artist-defined rain distribution and density, and then creates particles in the scene following these indications. No restrictions are imposed on the dimensions of the rain area, thus direct rendering approaches could rapidly overwhelm current computational capabilities with huge particle amounts. To solve this situation, we propose techniques that, in rendering time, adaptively sample the particles generated in order to only select the ones in the regions that really need to be simulated and rendered. Particle simulation is executed entirely in the graphics hardware. The algorithm proceeds by placing the particles in their updated coordinates. It then checks whether a particle is falling as a rain streak, it has reached the ground and it is a splash or, finally, if it should be discarded because it has entered a solid object of the scene. Different rendering techniques are used for each case. Complex illumination parameters are computed for rain streaks to select textures matching them. These textures are generated in a preprocess step and realistically simulate light when interacting with the optical properties of the water drops

Numerical Simulation of Surface Energy and Water Balances over a Semiarid Grassland Ecosystem in the West African Savanna

To understand surface energy exchange processes over the semiarid regions in West Africa, numerical simulations of surface energy and water balances were carried out using a one-dimensional multilayer atmosphere-SOil-VEGetation (SOLVEG) model for selected days of the dry and rainy seasons over a savanna grassland ecosystem in Sumbrungu in the Upper East region of Ghana. The measured Bowen ratio was used to partition the residual energy into the observed sensible heat flux () and latent heat flux (LE) in order to investigate the impact of the surface energy closure on model performance. The results showed that the model overall reproduced the diurnal changes in the observed energy fluxes, especially the net radiation (Rn), compared to half-hourly eddy covariance flux measurements, for the study periods. The performance measure in terms of the correlation coefficient (), centred root mean square error (RMSE), and normalized standard deviation (σ) between the simulated and LE and their corresponding uncorrected observed values ranged between R = 0.63–0.99 and 0.83–0.94, RMSE = 0.88–1.25 and 0.88–1.92, and = 0.95–2.23 and 0.13–2.82 for the dry and rainy periods respectively, indicating a moderate to good model performance. The partitioning of and LE by SOLVEG was generally in agreement with the observations during the dry period but showed clear discrepancies during the rainy period, particularly after rainfall events. Further sensitivity tests over longer simulation periods (e.g., 1 year) are required to improve model performance and to investigate seasonal exchanges of surface energy fluxes over the West African Savanna ecosystems in more details

Real-time Realistic Rain Rendering

Artistic outdoor filming and rendering need to choose specific weather conditions in order to properly trigger the audience reaction; for instance, rain, one of the most common conditions, is usually employed to transmit a sense of unrest. Synthetic methods to recreate weather are an important avenue to simplify and cheapen filming, but simulations are a challenging problem due to the variety of different phenomena that need to be computed. Rain alone involves raindrops, splashes on the ground, fog, clouds, lightnings, etc. We propose a new rain rendering algorithm that uses and extends present state of the art approaches in this field. The scope of our method is to achieve real-time renders of rain streaks and splashes on the ground, while considering complex illumination effects and allowing an artistic direction for the drops placement. Our algorithm takes as input an artist-defined rain distribution and density, and then creates particles in the scene following these indications. No restrictions are imposed on the dimensions of the rain area, thus direct rendering approaches could rapidly overwhelm current computational capabilities with huge particle amounts. To solve this situation, we propose techniques that, in rendering time, adaptively sample the particles generated in order to only select the ones in the regions that really need to be simulated and rendered. Particle simulation is executed entirely in the graphics hardware. The algorithm proceeds by placing the particles in their updated coordinates. It then checks whether a particle is falling as a rain streak, it has reached the ground and it is a splash or, finally, if it should be discarded because it has entered a solid object of the scene. Different rendering techniques are used for each case. Complex illumination parameters are computed for rain streaks to select textures matching them. These textures are generated in a preprocess step and realistically simulate light when interacting with the optical properties of the water drops

Real-time Physics Based Simulation for 3D Computer Graphics

Restoration of realistic animation is a critical part in the area of computer graphics. The goal of this sort of simulation is to imitate the behavior of the transformation in real life to the greatest extent. Physics-based simulation provides a solid background and proficient theories that can be applied in the simulation. In this dissertation, I will present real-time simulations which are physics-based in the area of terrain deformation and ship oscillations. When ground vehicles navigate on soft terrains such as sand, snow and mud, they often leave distinctive tracks. The realistic simulation of such vehicle-terrain interaction is important for ground based visual simulations and many video games. However, the existing research in terrain deformation has not addressed this issue effectively. In this dissertation, I present a new terrain deformation algorithm for simulating vehicle-terrain interaction in real time. The algorithm is based on the classic terramechanics theories, and calculates terrain deformation according to the vehicle load, velocity, tire size, and soil concentration. As a result, this algorithm can simulate different vehicle tracks on different types of terrains with different vehicle properties. I demonstrate my algorithm by vehicle tracks on soft terrain. In the field of ship oscillation simulation, I propose a new method for simulating ship motions in waves. Although there have been plenty of previous work on physics based fluid-solid simulation, most of these methods are not suitable for real-time applications. In particular, few methods are designed specifically for simulating ship motion in waves. My method is based on physics theories of ship motion, but with necessary simplifications to ensure real-time performance. My results show that this method is well suited to simulate sophisticated ship motions in real time applications

Integrated display and analysis tool for multi-variable radar data

Fall 2004.Also issued as author's thesis (M.S.) -- Colorado State University, 2005.Includes bibliographical references.Doppler and polarimetric radars provide valuable information about the kinematics and microphysics of storms. However, radar products, such as Doppler­ derived wind vectors and hydrometeor identification, which assist with in-depth analysis of storms, have not been readily available in (near) real-time. The goal of this project is to develop and integrate radar algorithms currently used in post¬ processing with meteorological observations to develop a near real-time integrated display and analysis tool for use in nowcasting. This software has been linked to and is now available for real-time radar operations at the CSU-CHILL radar facility. This methodology was also developed for a network of four Doppler radars, including one polarimetric radar, along the Northern Colorado front range. The four radars include two National Weather Service WSR-88D radars (KFTG and KCYS) and two research radars (PAWNEE and CSU-CHILL) operated by Colorado State University. These four radars form three dual-Doppler pairs, in which the radial velocities can be synthesized to obtain three-dimensional wind vectors. The analysis also incorporates algorithms for hydrometeor identification and rainfall rate estimation using the polarimetric measurements from CSU-CHILL, as well as ram rate calculation using standard midlatitude Z-R relationships. The software was successfully tested at the CSU-CHILL radar facility during the summer of 2004 using data from three of the radars. CHILL data were available within 3 minutes after a volume scan, WSR-88D was displayed approximately 12 minutes after the start of a volume scan, therefore the dual-Doppler winds lagged by 13-15 minutes after the start of the first volume scan. Among other things, users have the ability to zoom in and out of interesting radar features, change the grid resolution and origin, create vertical cross sections, contour data, and archive data as they use the software in real-time. Despite the lag time, the tool helped diagnose areas of intense rainfall and possible hail, updrafts, and wind field features such as mesocyclones and convergence lines. Two case studies from June 2004 are used to demonstrate the utility of the software in this thesis. The software was found to be a valuable resource for assisting scientists with the real-time analysis and visualization of copious amounts of data from a network of multi-variable radars. This tool could be especially useful during large field experiments, especially those in which one research aircraft requires guidance from ground-based radars.Sponsored by the National Science Foundation under grant ATM-0121546 and award no. 0313747

Organic aerosol and global climate modelling: a review

The present paper reviews existing knowledge with regard to Organic Aerosol (OA) of importance for global climate modelling and defines critical gaps needed to reduce the involved uncertainties. All pieces required for the representation of OA in a global climate model are sketched out with special attention to Secondary Organic Aerosol (SOA): The emission estimates of primary carbonaceous particles and SOA precursor gases are summarized. The up-to-date understanding of the chemical formation and transformation of condensable organic material is outlined. Knowledge on the hygroscopicity of OA and measurements of optical properties of the organic aerosol constituents are summarized. The mechanisms of interactions of OA with clouds and dry and wet removal processes parameterisations in global models are outlined. This information is synthesized to provide a continuous analysis of the flow from the emitted material to the atmosphere up to the point of the climate impact of the produced organic aerosol. The sources of uncertainties at each step of this process are highlighted as areas that require further studies

Continental-scale impacts of intra-seasonal rainfall variability on simulated ecosystem responses in Africa

Climate change is expected to modify intraseasonal rainfall variability, arising from shifts in rainfall frequency, intensity and seasonality. These intra-seasonal changes are likely to have important ecological impacts on terrestrial ecosystems. Yet, quantifying these impacts across biomes and large climate gradients is largely missing. This gap hinders our ability to better predict ecosystem services and their responses to climate change, especially for arid and semi-arid ecosystems. Here we use a synthetic weather generator and an independently validated vegetation dynamic model (SEIB-Dynamic Global Vegetation Model, DGVM) to virtually conduct a series of "rainfall manipulation experiments" to study how changes in the intra-seasonal rainfall variability affect continent-scale ecosystem responses across Africa. We generate different rainfall scenarios with fixed total annual rainfall but shifts in (i) frequency vs. intensity, (ii) rainy season length vs. frequency, (iii) intensity vs. rainy season length. These scenarios are fed into SEIB-DGVM to investigate changes in biome distributions and ecosystem productivity. We find a loss of ecosystem productivity with increased rainfall frequency and decreased intensity at very low rainfall regimes ( 1800mm year-11) where radiation limitation prevents further productivity gains. This result reconciles seemingly contradictory findings in previous field studies on the impact of rainfall frequency/intensity on ecosystem productivity. We also find that changes in rainy season length can yield more dramatic ecosystem responses compared with similar percentage changes in rainfall frequency or intensity, with the largest impacts in semi-arid woodlands. This study demonstrates that intra-seasonal rainfall characteristics play a significant role in influencing ecosystem function and structure through controls on ecohydrological processes. Our results suggest that shifts in rainfall seasonality have potentially large impacts on terrestrial ecosystems, and these understudied impacts should be explicitly examined in future studies of climate impacts

Numerical Simulation of Surface Energy and Water Balances over a Semiarid Grassland Ecosystem in the West African Savanna

To understand surface energy exchange processes over the semiarid regions in West Africa, numerical simulations of surface energy and water balances were carried out using a one-dimensional multilayer atmosphere-SOil-VEGetation (SOLVEG) model for selected days of the dry and rainy seasons over a savanna grassland ecosystem in Sumbrungu in the Upper East region of Ghana. The measured Bowen ratio was used to partition the residual energy into the observed sensible heat flux (H) and latent heat flux (LE) in order to investigate the impact of the surface energy closure on model performance. The results showed that the model overall reproduced the diurnal changes in the observed energy fluxes, especially the net radiation (Rn), compared to half-hourly eddy covariance flux measurements, for the study periods. The performance measure in terms of the correlation coefficient (R), centred root mean square error (RMSE), and normalized standard deviation (σ) between the simulated H and LE and their corresponding uncorrected observed values ranged between R = 0.63–0.99 and 0.83–0.94, RMSE = 0.88–1.25 and 0.88–1.92, and σ = 0.95–2.23 and 0.13–2.82 for the dry and rainy periods respectively, indicating a moderate to good model performance. The partitioning of H and LE by SOLVEG was generally in agreement with the observations during the dry period but showed clear discrepancies during the rainy period, particularly after rainfall events. Further sensitivity tests over longer simulation periods (e.g., 1 year) are required to improve model performance and to investigate seasonal exchanges of surface energy fluxes over the West African Savanna ecosystems in more details

Modelling the potential of integrated vegetation bands (IVB) to retain stormwater runoff on steep hillslopes of Southeast Queensland, Australia

Rainfall intensity is predicted to increase under a changing climate, leading to increased risks of hillslope erosion, downstream sedimentation and flooding. For many catchments used for grazing and agricultural land uses, it will become increasingly important to maintain ecohydrological functioning despite climatic extremes. One means to achieve this is through strategic reforestation using locally endemic species, in spatial configurations that effectively intercept, retain or and redistribute overland flows. This paper adopts a modelling approach for investigating the potential of one such design termed “integrated vegetation bands” (IVB), to increase the retention of runoff across steep hillslopes, particularly in the sub-tropics where rainstorms are becoming increasingly intense. A spatially distributed simulation model (MIKE-SHE) was applied to a steep, grazed catchment (Maronghi Creek catchment, Southeast Queensland, Australia) to compare stormwater runoff characteristics between: (1) the existing pasture land cover; and (2) a series of hypothetical IVB added across this pasture land. The IVB were approximately 20 m wide, and configured at 5% gradient towards ridgelines. Results for estimates of overland flow depth and infiltration (spatial), and accumulative water balance (temporal), confirm that the area of hillslope retaining > 10 mm/day more runoff increased by 22% under IVB compared to the pasture land use. Excluding the IVB themselves, the area of hillslope where runoff retention increased was 11%. During the most intense rainfall, IVB held up to 25% greater water depth and had 10% greater infiltration at the hillslope scale. At the sub-catchment scale, discharge decreased by 7% and infiltration increased by 23%. The findings for sub-tropical landscapes presented here are consistent with studies conducted in temperate regions. Based on the results of this preliminary modelling work, the IVB concept has been established as a paired-catchment field trial in a high rainfall catchment in Southeast Queensland, Australia